病毒蛋白亚细胞定位的综合预测和解释

Xiyu Liu
{"title":"病毒蛋白亚细胞定位的综合预测和解释","authors":"Xiyu Liu","doi":"10.1145/3375923.3375950","DOIUrl":null,"url":null,"abstract":"Determining the subcellular localization of viral proteins is indispensable for understanding the activity of the virus and inferring viral protein functions. Although previous studies about predicting viral protein subcellular localization have been developed, they often have the following disadvantages: (i) only focusing on a part of proteins of a species (ii) not considering the presence of multi-location proteins and (iii) lacking interpretability for the results. To address these problems, this paper is firstly predicting all the subcellular localization of the whole viral proteome in the UniProtKB and is interpretable for the results. This paper gives high prediction accuracy for the single-location and multi-location viral proteins by the FUEL-mLoc predictor. More importantly, we did deeply analysis and interpretation of the subcellular localization of all viral proteins. Finally, we have found some essential GO terms which are interpretable for the results and are significant in predicting the subcellular localization of the viral proteins.","PeriodicalId":20457,"journal":{"name":"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive Prediction and Interpretation of Viral Protein Subcellular Localization\",\"authors\":\"Xiyu Liu\",\"doi\":\"10.1145/3375923.3375950\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Determining the subcellular localization of viral proteins is indispensable for understanding the activity of the virus and inferring viral protein functions. Although previous studies about predicting viral protein subcellular localization have been developed, they often have the following disadvantages: (i) only focusing on a part of proteins of a species (ii) not considering the presence of multi-location proteins and (iii) lacking interpretability for the results. To address these problems, this paper is firstly predicting all the subcellular localization of the whole viral proteome in the UniProtKB and is interpretable for the results. This paper gives high prediction accuracy for the single-location and multi-location viral proteins by the FUEL-mLoc predictor. More importantly, we did deeply analysis and interpretation of the subcellular localization of all viral proteins. Finally, we have found some essential GO terms which are interpretable for the results and are significant in predicting the subcellular localization of the viral proteins.\",\"PeriodicalId\":20457,\"journal\":{\"name\":\"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3375923.3375950\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 6th International Conference on Biomedical and Bioinformatics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3375923.3375950","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

确定病毒蛋白的亚细胞定位是了解病毒活性和推断病毒蛋白功能的必要条件。虽然之前关于预测病毒蛋白亚细胞定位的研究已经发展起来,但它们往往存在以下缺点:(i)只关注一个物种的一部分蛋白质(ii)没有考虑多位置蛋白质的存在(iii)缺乏结果的可解释性。为了解决这些问题,本文首先在UniProtKB中预测了整个病毒蛋白质组的所有亚细胞定位,并对结果进行了解释。本文给出了FUEL-mLoc预测器对单位点和多位点病毒蛋白具有较高的预测精度。更重要的是,我们对所有病毒蛋白的亚细胞定位进行了深入的分析和解释。最后,我们发现了一些基本的氧化石墨烯术语,这些术语可以解释结果,并且在预测病毒蛋白的亚细胞定位方面具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Comprehensive Prediction and Interpretation of Viral Protein Subcellular Localization
Determining the subcellular localization of viral proteins is indispensable for understanding the activity of the virus and inferring viral protein functions. Although previous studies about predicting viral protein subcellular localization have been developed, they often have the following disadvantages: (i) only focusing on a part of proteins of a species (ii) not considering the presence of multi-location proteins and (iii) lacking interpretability for the results. To address these problems, this paper is firstly predicting all the subcellular localization of the whole viral proteome in the UniProtKB and is interpretable for the results. This paper gives high prediction accuracy for the single-location and multi-location viral proteins by the FUEL-mLoc predictor. More importantly, we did deeply analysis and interpretation of the subcellular localization of all viral proteins. Finally, we have found some essential GO terms which are interpretable for the results and are significant in predicting the subcellular localization of the viral proteins.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
DMBA Induction Increases H-Ras Gene Expression and Decreases CD8 Count in Sprague Dawley Rats Predicting the Types of Striking and Thrusting Motions by using Deep Learning A World Camera for Recording the Game Tactics in Martial Arts using Bamboo Swords In Vitro Safety Assessment and Permeation Study of Topical Lidocaine Solution for Ocular Administration An Investigation into Audio Features and DTW Algorithms for Infant Cry Classification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1